Package inclusion in R core implementation

Conversely, what is the process to remove a package from core R? It seems
to me some (many?) of the packages included are there more out of
historical accident rather than any technical need to be in the core
distribution. Having them as a core (or recommended) package makes them
harder update independently to R and makes testing, development and
contribution more cumbersome.

On Fri, Mar 1, 2019 at 4:35 AM Morgan Morgan <morgan.emailbox at gmail.com>
wrote:

Hi,

It sometimes happens that some packages get included to R like for example
the parallel package.

I was wondering if there is a process to decide whether or not to include a
package in the core implementation of R?

For example, why not include the Rcpp package, which became for a lot of
user the main tool to extend R?

What is our view on the (not so well known) dotCall64 package which is an
interesting alternative for extending R?

Thank you
Best regards,
Morgan

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As the original coder (in mid 1970s) of BFGS, CG and Nelder-Mead in
optim(), I've
been pushing for some time for their deprecation. They aren't "bad", but
we have
better tools, and they are in CRAN packages. Similarly, I believe other
optimization
tools in the core (optim::L-BFGS-B, nlm, nlminb) can and should be moved to
packages (there are already 2 versions at least of LBFGS that I and Matt
Fidler
are merging). And optim::SANN does not match any usual expectations of
users.

I'm sure there are other tools for other tasks that can and should move to
packages
to streamline the work of our core team. However, I can understand that
there is this
awkward issue of actually doing this. I know I'm willing to help with
preparing
"Transition Guide" documentation and scripts, and would be surprised if
there are
not others. R already has a policy of full support only for current
version, so
hanging on to antique tools (the three codes at the top are based on
papers all
of which now qualify for >50 years old) seems inconsistent with other
messages.

For information: I'm coordinating a project to build understanding of what
older algorithms are in R as the histoRicalg project. See
https://gitlab.com/nashjc/histoRicalg. We welcome participation.

Best, JN

On 2019-03-04 7:59 a.m., Jim Hester wrote:

Conversely, what is the process to remove a package from core R? It seems
to me some (many?) of the packages included are there more out of
historical accident rather than any technical need to be in the core
distribution. Having them as a core (or recommended) package makes them
harder update independently to R and makes testing, development and
contribution more cumbersome.

On Fri, Mar 1, 2019 at 4:35 AM Morgan Morgan <morgan.emailbox at gmail.com>
wrote:

Hi,

It sometimes happens that some packages get included to R like for

example

the parallel package.

I was wondering if there is a process to decide whether or not to

include a

package in the core implementation of R?

For example, why not include the Rcpp package, which became for a lot of
user the main tool to extend R?

What is our view on the (not so well known) dotCall64 package which is

an

interesting alternative for extending R?

Thank you
Best regards,
Morgan

On Mon, Mar 4, 2019 at 5:01 PM J C Nash <profjcnash at gmail.com <mailto:profjcnash at gmail.com>> wrote:

    As the original coder (in mid 1970s) of BFGS, CG and Nelder-Mead in optim(), I've
    been pushing for some time for their deprecation. They aren't "bad", but we have
    better tools, and they are in CRAN packages. Similarly, I believe other optimization
    tools in the core (optim::L-BFGS-B, nlm, nlminb) can and should be moved to
    packages (there are already 2 versions at least of LBFGS that I and Matt Fidler
    are merging). And optim::SANN does not match any usual expectations of users.

    I'm sure there are other tools for other tasks that can and should move to packages
    to streamline the work of our core team. However, I can understand that there is this
    awkward issue of actually doing this. I know I'm willing to help with preparing
    "Transition Guide" documentation and scripts, and would be surprised if there are
    not others. R already has a policy of full support only for current version, so
    hanging on to antique tools (the three codes at the top are based on papers all
    of which now qualify for >50 years old) seems inconsistent with other messages.

    For information: I'm coordinating a project to build understanding of what
    older algorithms are in R as the histoRicalg project. See
    https://gitlab.com/nashjc/histoRicalg. We welcome participation.

    Best, JN

    On 2019-03-04 7:59 a.m., Jim Hester wrote:

    > Conversely, what is the process to remove a package from core R? It seems
    > to me some (many?) of the packages included are there more out of
    > historical accident rather than any technical need to be in the core
    > distribution. Having them as a core (or recommended) package makes them
    > harder update independently to R and makes testing, development and
    > contribution more cumbersome.
    >
    > On Fri, Mar 1, 2019 at 4:35 AM Morgan Morgan <morgan.emailbox at gmail.com <mailto:morgan.emailbox at gmail.com>>
    > wrote:
    >

    >> Hi,
    >>
    >> It sometimes happens that some packages get included to R like for example
    >> the parallel package.
    >>
    >> I was wondering if there is a process to decide whether or not to include a
    >> package in the core implementation of R?
    >>
    >> For example, why not include the Rcpp package, which became for a lot of
    >> user the main tool to extend R?
    >>
    >> What is our view on the (not so well known) dotCall64 package which is an
    >> interesting alternative for extending R?
    >>
    >> Thank you
    >> Best regards,
    >> Morgan
    >>

I have No arguments with updating code to more correct or modern versions, but I think that as a design decision, base R
should have optimization routines as opposed to it being an external package which conceptually could be orphaned. Or at
least some package gets made recommended and adopted by R core.

Thank you,

Avi
-- 
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Conversely, what is the process to remove a package from core R? It seems
to me some (many?) of the packages included are there more out of
historical accident rather than any technical need to be in the core
distribution. Having them as a core (or recommended) package makes them
harder update independently to R and makes testing, development and
contribution more cumbersome.

On Fri, Mar 1, 2019 at 4:35 AM Morgan Morgan <morgan.emailbox at gmail.com>
wrote:

Hi,

It sometimes happens that some packages get included to R like for example
the parallel package.

I was wondering if there is a process to decide whether or not to include a
package in the core implementation of R?

For example, why not include the Rcpp package, which became for a lot of
user the main tool to extend R?

What is our view on the (not so well known) dotCall64 package which is an
interesting alternative for extending R?

Thank you
Best regards,
Morgan

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I concur with Avraham that capabilities need to be ensured e.g., in recommended
packages. I should have mentioned that. My concern is that the core should be
focused on the programming language aspects. The computational math and some of the more
intricate data management could better be handled by folk outside the core.

JN